Optimal Gabor filter design for texture segmentation using stochastic optimization

Tsai, Du Ming; Wu, Song; Chen, Mu-Chen

doi:10.1016/s0262-8856(00)00078-0

Cited by 55 publications

(34 citation statements)

References 31 publications

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“…And research show that Gabor filters mimic the biological perception of texture and share many properties with the human visual system (Raghunathan and Acton, 2000). This property of Gabor filters makes them capable of reaching the minimum bound for simultaneous localization in the spatial and spatial/frequency domains (Tsai et al, 2001). Moreover Gabor filters bank composing of a set of kernels can provide a complete cover of spatial/frequency domain so that it can generate a versatile model for texture description of various land cover.…”

Section: Laws Masksmentioning

confidence: 97%

“…Gabor decompositions have been proposed as an analysis tool for texture (Bigun and du Buf, 1994) which is inspired by the psychological research of the human visual system (Malik and Perona, 1990). Gabor filters are employed in many researches, such as texture segmentation (Tsai et al, 2001;Weldon et al, 1996), texture classification (Manjunath and Ma, 1996) and texture extraction (Kruizinga and Petkov, 1999;Koperski et al, 2002). Koperski et al (2002); Shapiro and Stockman (1991) applies Gabor wavelets in a system for data mining of remotely sensed images.…”

Section: Introductionmentioning

confidence: 99%

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Land Cover Change Detection Using Texture Analysis

Wu¹

2010

Journal of Computer Science

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Problem statement: It is an important task to detect land cover changes from remotely sensed data for environmental monitoring. Although there are some applications of visual textures to the land use, they are limited to a few land cover categories with the application of one texture measure. Since land cover types are complex and often the integration of various objects, applying one texture measure to characterize land cover types is not possible. Approach: This study presented two types of texture measures for land cover types and applies them to detect possible land cover changes by discriminant analysis. The texture information of land cover types were modeled by different texture extraction methods, Laws Masks and Gabor filters. Laws Masks were designed to characterize the features in local neighborhoods. Moreover information in multi-channel of the spatial frequency domain was modeled by the Gabor filters with different orientations and spatial periods. The performance of these texture measures to detect land cover changes were evaluated by the discriminant analysis. Based on the transition matrix of land cover, the detection of land cover changes becomes to separate the land cover pair which is possible to derive conversion between them. The discriminant analysis was designed on a statistical test, which determines the contribution of the features attending the discrimination. Results: The experiments showed that this approach is capable of detecting changes and different measures are suitable to detect different changes. Conclusion: The experiment presented a textural guide for the change detection.

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Section: Laws Masksmentioning

confidence: 97%

Section: Introductionmentioning

confidence: 99%

Land Cover Change Detection Using Texture Analysis

Wu¹

2010

Journal of Computer Science

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“…Bodnarova et al 15) proposed applying a Fisher cost function to select a subset of Gabor functions based on the mean and standard deviation of the template feature images to perform textile flaw detection. Tsai et al 16) used a single Gabor filter for multiple texture segmentation using a systematic optimization algorithm. Later Tsai and Lin 17) developed a fast defect detection algorithm for textured surfaces using 1D Gabor filters.…”

Section: Detection Of Pinholes In Steel Slabs Using Gabor Filter Combmentioning

confidence: 99%

Detection of Pinholes in Steel Slabs Using Gabor Filter Combination and Morphological Features

et al. 2017

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In this paper, an algorithm for detecting pinholes was proposed. Pinholes are very tiny holes generated in the surfaces of scarfed slabs. To detect various sizes of pinholes, the Gabor filter combination was applied. A new image segmentation method was proposed in pre-processing. To reduce the number of pseudo-defects, dual thresholding method was used. We have increased the performance of classification by adding new morphological features to general texture based features. To evaluate the performance of proposed algorithm, an images obtained in real production line were used.

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“…Texture segmentation with stochastic optimization [12] and Texture segmentation using optimized separation [13] are some examples in the literature for supervised segmentation. For any textured analysis, the main conceptual difficulties are to define a texture measure and a texture classification method [14].…”

Section: Introductionmentioning

confidence: 99%

Segmentation of Multi-Textured Images using Optimized Local Ternary Patterns

Raja¹,

Sadasivam²

2014

IJCA

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Texture segmentation is a process of segmenting an image into differently textured regions. This paper is aimed at the segmentation of multitextured images by using Optimized Local Ternary Patterns (OLTP), a new texture model which is recently proposed for texture analysis. This paper uses unsupervised texture segmentation method with the application of optimized local ternary patterns for finding the dissimilarity of adjacent image regions during the segmentation process. The performance of this recently proposed texture measure OLTP is evaluated, compared with other texture models Texture Spectrum (TS) and Local Binary Patterns (LBP) and found to be the best.

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Optimal Gabor filter design for texture segmentation using stochastic optimization

Cited by 55 publications

References 31 publications

Land Cover Change Detection Using Texture Analysis

Land Cover Change Detection Using Texture Analysis

Detection of Pinholes in Steel Slabs Using Gabor Filter Combination and Morphological Features

Segmentation of Multi-Textured Images using Optimized Local Ternary Patterns

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